CN107087173B - A kind of video encoding optimization method of content oriented analysis - Google Patents

A kind of video encoding optimization method of content oriented analysis Download PDF

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CN107087173B
CN107087173B CN201710228418.1A CN201710228418A CN107087173B CN 107087173 B CN107087173 B CN 107087173B CN 201710228418 A CN201710228418 A CN 201710228418A CN 107087173 B CN107087173 B CN 107087173B
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distortion
content analysis
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content
analysis
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CN107087173A (en
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朱策
刘宇洋
毛敏
宋方良
张翔
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University of Electronic Science and Technology of China
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/146—Data rate or code amount at the encoder output
    • H04N19/147—Data rate or code amount at the encoder output according to rate distortion criteria

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  • Compression Or Coding Systems Of Tv Signals (AREA)

Abstract

The invention belongs to technical field of video compression, particularly relate to a kind of video encoding optimization method of content oriented analysis.The method of the present invention includes four parts: content analysis distortion model, content analysis distortion prediction model, rate misalignment model and rate-distortion optimization.Distortion model, influence of the quantitation video compression artefacts to content analysis algorithms performance are analyzed by content construction；It is analyzed and is distorted using compression artefacts SAD (Sum of Absolute Difference) predictive content；Using the relationship between e index Function Fitting content analysis distortion and code rate；Content analysis distortion is introduced into rate-distortion optimization, to minimize pixel distortion and content analysis distortion as optimization aim, improves existing Rate-distortion optimization method.Content analysis distortion is eventually reduced, influence of the video compress distortion to content analysis algorithms is weakened.

Description

A kind of video encoding optimization method of content oriented analysis
Technical field
The invention belongs to technical field of video compression, the Video coding for particularly relating to a kind of content oriented analysis is excellent Change method.
Background technique
With the progress and development of video communication technology, video data is in explosive growth, especially in field of video monitoring, The monitor video data of the super large scale of construction are compressed, are transmitted to server end, carry out content analysis by computer, reach various mesh , such as moving-target detection, recognition of face, behavioural analysis.Nowadays, most of video encoders are to maximize human eye vision quality For optimization aim, compression artefacts is caused to reduce the performance of subsequent content parser.In the past few decades, researchers propose Many methods reduce influence of the compression artefacts to parser, and wherein most is both for saving local feature region.
Chao and Steinbac proposes a kind of rate-distortion model based on SIFT feature matching degree, and in static image It is verified in compression standard JPEG, the results showed that, it can save crucial SIFT feature under the conditions of low bit- rate, but this method Need to consume additional bit to transmit SIFT feature description son (J.S.Chao and E.Steinbach, " Preserving SIFT features in JPEG-encoded images,”IEEE International Conference on Image Processing,Brussels,Belgium,Sept.2011,pp.301-304.).Baroffio et al. is for the part extracted Feature (such as SIFT, SURF) proposes a kind of new video coding framework, and the frame is interior using frame and inter-frame mode is to extraction Characteristic information is encoded, but this method only transmits local feature description's, therefore can not obtain video figure in decoding end As information (L.Baroffio, M.Cesana, A.Redondi, M.Tagliasacchi, and S.Tubaro, " Coding visual features extracted from video sequences”,IEEE Transactions on Image Processing,vol.23,no.5,pp.2262-2276,May 2014.).The above method is mostly directed to the view of characteristic point preservation Frequency compression method not can effectively solve the equilibrium problem of code rate, compression artefacts and content analysis distortion.
Summary of the invention
The present invention is the influence to can reduce video compress distortion to content analysis, proposes what a kind of content oriented was analyzed Video encoding optimization method, it is intended to solve the equilibrium problem of code rate, compression artefacts and analysis distortion.
The technical scheme is that
A kind of video encoding optimization method of content oriented analysis, which comprises the following steps:
S1, content analysis distortion D is definedATo quantitation video compression artefacts DPInfluence to content analysis algorithms, under Column formula (1) calculates content analysis and is distorted DA, compression artefacts DPIt can be obtained according to formula (2) or formula (3)；
DA=| Do-Dc| (formula 1)
SAD=∑ | recpixel-orgpixel | (formula 3)
Wherein, DoFor the content analysis algorithms on uncompressed video analysis as a result, DcFor content on video upon compression point Analyse the analysis result of algorithm；Respixel is reconstructed pixel, and orgpixel is original pixels, and Imagesize is picture size；
S2, D is distorted according to the content analysis that step S1 is obtainedA, construction content analysis distortion DARelationship between code rate R, Creation rate misalignment model is indicated with formula (4)；
In formula 4, C1And C2For constant；
S3, the content analysis according to obtained in step S1 are distorted DAWith compression artefacts DP, optimization aim is constructed with formula (5) Equation；
min DP+αDA s.t.R≤RT(formula 5)
Wherein, α is weight factor, and R is code rate, RTFor total bandwidth.It can be seen from the rate misalignment model that step S2 is created Content analysis is distorted DACode rate R can be led, while according to rate-distortion model in HEVC encoder it is found that compression artefacts DPTo code rate R It can lead, therefore using method of Lagrange multipliers, (6) obtain optimization solution according to the following formula:
min{Jnew},where Jnew=DP+αDA+λnewR (formula 6)
Wherein λnewFor Lagrange multiplier.
The beneficial effects of the present invention are: being improved existing with minimizing pixel distortion and content analysis distortion as optimization aim Rate-distortion optimization method reduces influence of the video compress distortion to content analysis algorithms.
Detailed description of the invention
Fig. 1 is that video content analysis distortion obtains flow chart in the present invention；
Fig. 2 is the statistical result of analysis distortion and SAD；
Fig. 3 is the statistical result of analysis distortion and code rate；(a) (b) (c) (d) is respectively the statistics of 4 test videos in figure As a result；
Fig. 4 is comparative result figure；(a) (b) (c) (d) is respectively the comparative result figure of 4 test videos in figure.
Appended drawing reference: ordinate bpp is expressed as unit pixel bit number (bit per pixel) in Fig. 3, by following equation It is calculated；
Wherein R is total bit number, and f is the frame per second of video, and w is the width of video, and h is the height of video.
Specific embodiment
With reference to the accompanying drawings and examples, the technical schemes of the invention are described in detail:
Embodiment
By taking moving-target detects as an example, comprising the following steps:
1, from PETS2006 (www.cvg.cs.rdg.ac.uk/PETS2006) and CAVIAR (www.dai.ed.ac.uk/ Homes/rbf/CAVIAR/ 4 sections of monitor videos) are chosen in database, and (wherein 3 sections of videos are indoor scene, and in addition 1 section is room Outer scene) it is used as training data, using document (B.Lei, A.Leonardis, and B.Schiele, " Robust object detection with interleaved categorization and segmentation,”Intl.J.Computer Vision, vol.77, no.1, pp.259-289,2008.) in moving-target detection algorithm, record testing result.
2, HEVC encoder quantization parameter QP (4-41) is set, obtains the compression of 38 different qualities of 4 sections of training videos Video runs identical detection algorithm, records testing result.
3, as a result, using the testing result in above-mentioned 1 as reference, the testing result in 2 uses statistical experiment as a comparison F-measure evaluation index (Y.Dhome, N.Tronson, A.Vacavant, T.Chateau, C.Gabard, Y.Goyat, D.Gruyer,“A benchmark for background subtraction algorithms in monocular vision:a comparative study,”International Conference on Image Processing, Theory, Tools and Applications, 2010.) quantitative analysis distortion:
Wherein,It is distorted for the analysis of a frame,It is distorted for the average analysis of video, FiF-measure for a frame is commented Valence index, n are the frame number of video.
4, it is distorted using formula (9) Fitting AnalysisWith the functional relation of compression artefacts SAD.Statistical result showed is in Fig. 2 In, k 4.1x10-7, b 0.01.Using the Rate-distortion optimization method pretreatment in original HEVC encoder, compression artefacts are obtained SAD is used to forecast analysis and is distorted
5, using the functional relation of formula (4) fitting content analysis distortion and code rate R.Statistical result showed is public in Fig. 3 Parameter C in formula (4)1And C2Respectively 47, -81.8.
6, parameter alpha (0.2) is set, using the optimization algorithm in the present invention, moving-target detection algorithm, record are run after compression Testing result.
Fig. 4 illustrates the performance comparison figure of method of the invention with original video Encoding Optimization, it can be seen that this hair Optimization method in bright can effectively reduce content analysis distortion, weaken influence of the video compress to content analysis algorithms.

Claims (1)

1. a kind of video encoding optimization method of content oriented analysis, which comprises the following steps:
S1, content analysis distortion D is definedATo quantitation video compression artefacts DPInfluence to content analysis algorithms, according to following public affairs Formula (1) calculates content analysis and is distorted DA, compression artefacts DPIt is obtained according to formula (2) or formula (3):
DA=| Do-Dc| (formula 1)
SAD=∑ | recpixel-orgpixel | (formula 3)
Wherein, DoFor the content analysis algorithms on uncompressed video analysis as a result, DcIt is calculated for content analysis on video upon compression The analysis result of method；Recpixel is reconstructed pixel, and orgpixel is original pixels, and Imagesize is picture size；
S2, D is distorted according to the content analysis that step S1 is obtainedA, construction content analysis distortion DARelationship between code rate R, creation Rate misalignment model is indicated with formula (4)；
In formula 4, C1And C2For constant；
S3, the content analysis according to obtained in step S1 are distorted DAWith compression artefacts DP, optimization aim equation is constructed with formula (5)；
Wherein, α is weight factor, and R is code rate, RTFor total bandwidth；By the step S2 rate misalignment model created it can be concluded that, content Analysis distortion DACode rate R can be led, while according to rate-distortion model in HEVC encoder it is found that compression artefacts DPIt can to code rate R It leads, using method of Lagrange multipliers, (6) obtain optimization solution according to the following formula:
min{Jnew},where Jnew=DP+αDA+λnewR (formula 6)
Wherein λnewFor Lagrange multiplier.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101014128A (en) * 2007-02-02 2007-08-08 清华大学 Method for quick estimating rate and distortion in H.264/AVC video coding
EP1863288A2 (en) * 2006-05-30 2007-12-05 Medison Co., Ltd. EBCOT based image compressing method
CN101521819A (en) * 2008-02-27 2009-09-02 深圳市融合视讯科技有限公司 Method for optimizing rate distortion in video image compression

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1863288A2 (en) * 2006-05-30 2007-12-05 Medison Co., Ltd. EBCOT based image compressing method
CN101014128A (en) * 2007-02-02 2007-08-08 清华大学 Method for quick estimating rate and distortion in H.264/AVC video coding
CN101521819A (en) * 2008-02-27 2009-09-02 深圳市融合视讯科技有限公司 Method for optimizing rate distortion in video image compression

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